Do We Need More Training Data?

Keywords

Template, Regularization (linguistics), Feature (linguistics), Training (meteorology), Pattern recognition (psychology)

References

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Cited by

• Visualizing Object Detection FeaturesCarl Vondrick, Aditya Khosla, Hamed Pirsiavash — 2015
• The Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural NetworksBabak Saleh, Ahmed Elgammal, Jacob Feldman — 2016
• Machine-learning methods in the classification of water bodiesMarek Sołtysiak, Marcin Blachnik, Dominika Dąbrowska — 2016
• Efficient object detection using convolutional neural network-based hierarchical feature modelingByungjae Lee, Enkhbayar Erdenee, Songguo Jin — 2016
• Incorporating Prototype Theory in Convolutional Neural NetworksBabak Saleh, Ahmed Elgammal, Jacob Feldman — 2016
• Keypoints Detection and Feature Extraction: A Dynamic Genetic Programming Approach for Evolving Rotation-Invariant Texture Image DescriptorsHarith Al-Sahaf, Mengjie Zhang, Ausama Al-Sahaf — 2017
• Asynchronous Data Aggregation for Training End to End Visual Control NetworksMathew Monfort, Matthew Johnson, Aude Oliva — 2017
• Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection DatasetZachary Pezzementi, Trenton Tabor, Peiyun Hu — 2017
• Multi-radial LBP Features as a Tool for Rapid Glomerular Detection and Assessment in Whole Slide Histopathology ImagesOlivier Simon, Rabi Yacoub, Sanjay Jain — 2017
• Learning to Model the TailYu-Xiong Wang, Deva Ramanan, Martial Hebert — 2017
• Unsupervised Machine Learning for Networking: Techniques, Applications and Research ChallengesMuhammad Usama, Junaid Qadir, Aunn Raza — 2017
• Studying the Effects of Training Data on Machine Learning-Based Procedural Content GenerationSam Snodgrass, Adam Summerville, Santiago Ontañón — 2021
• Classification du texte numérique et numérisé. Approche fondée sur les algorithmes d'apprentissage automatique. (Text and Image based classification of documents using machine and representation learning)Karim Sayadi — 2017
• Comparing apples and oranges: Off‐road pedestrian detection on the National Robotics Engineering Center agricultural person‐detection datasetZachary Pezzementi, Trenton Tabor, Peiyun Hu — 2018
• Learning Profiles in Duplicate Question DetectionChakaveh Saedi, João Rodrigues, João Silva — 2017
• Machine Learning to Discover and Optimize MaterialsConrad W. Rosenbrock — 2017
• Challenging Images For Minds and MachinesAmir Rosenfeld, John K. Tsotsos — 2018
• Deep super-class learning for long-tail distributed image classificationYucan Zhou, Qinghua Hu, Yu Wang — 2018
• Semantic Feature Augmentation in Few-shot LearningZitian Chen, Yanwei Fu, Yinda Zhang — 2018
• Object detection at 200 Frames Per SecondRakesh Mehta, Cemalettin Öztürk — 2018

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